Smart Technologies for Water Sewage Systems and Decision-Making with Circular Spherical Fuzzy Framework

Abrar Hussain; Muhammad Ahmad; Kifayat Ullah; Zeeshan Ali; Oumaima Saidani

Authors

Abrar Hussain 1) College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China; 2) College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, China Author https://orcid.org/0000-0003-2289-7464
Muhammad Ahmad Department of Mathematics, Riphah International University (Lahore Campus), Lahore, Pakistan Author https://orcid.org/0009-0006-5516-7897
Kifayat Ullah 1) Department of Mathematics, Riphah International University (Lahore Campus), Lahore, Pakistan; 2) Department of Mathematics, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India Author https://orcid.org/0000-0002-1438-6413
Zeeshan Ali Department of Information Management, National Yunlin University of Science and Technology, Yunlin, Taiwan Author https://orcid.org/0009-0002-3443-2840
Oumaima Saidani Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia Author https://orcid.org/0000-0001-9520-3174

Keywords:

Circular spherical fuzzy set, Dombi aggregation operators, Water sewage system, Artificial intelligence and decision support system

Abstract

Smart technologies play an increasingly attractive and transformative role in modern water and sewage systems, particularly under uncertain and dynamic environments. By integrating sensors, Internet of Things (IoT) devices, and artificial intelligence, these technologies enable real-time monitoring and adaptive control of complex water networks. To handle uncertainties such as fluctuating demand, climate variability, and data incompleteness, we develop an improved decision-making (DM) model using the circular spherical fuzzy set (Cr-SFS). The Cr-SFS is a flexible structure for managing uncertainty in human opinions. This article presents a new class of aggregation operators, namely the circular spherical fuzzy Dombi weighted averaging (Cr-SFDWA), circular spherical fuzzy Dombi weighted geometric (Cr-SFDWG), circular spherical fuzzy Dombi ordered weighted averaging (Cr-SFDOWA), and circular spherical fuzzy Dombi ordered weighted geometric (Cr-SFDOWG) operators. The realistic qualities and exceptional cases of these operators are also clarified through appropriate properties. An intelligent decision-making methodology for the MADM problem is applied to resolve real-life applications. A numerical example is presented to investigate an appropriate artificial intelligence-based water sewage system using decision analysis models and mathematical approaches. Moreover, a comprehensive comparison method is presented to illustrate the effectiveness and relevance of the proposed aggregation relative to existing approaches. The study is concluded with a summary of the main findings and the potential contributions of advanced decision-making techniques.

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